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Gemma is a family of lightweight, state-of-the art open models built from research and technology used to create Google Gemini models. They are text-to-text, decoder-only large language models, available in English, with open weights, pre-trained variants, and instruction-tuned variants. For more details, please check out the following links: Gemma on Google AI Gemma on Kaggle Gemma on Vertex AI M
Typograms (short for typographic diagrams) is a lightweight image format (text/typogram) useful for defining simple diagrams in technical documentation, originally developed here. See it in action here: https://google.github.io/typograms/ Like markdown, typograms is heavily inspired by pre-existing conventions found in ASCII diagrams. A small set of primitives and rules to connect them is defined,
This document is for engineers and researchers (both individuals and teams) interested in maximizing the performance of deep learning models. We assume basic knowledge of machine learning and deep learning concepts. Our emphasis is on the process of hyperparameter tuning. We touch on other aspects of deep learning training, such as pipeline implementation and optimization, but our treatment of tho
The basic architecture of the Lyra codec is quite simple. Features are extracted from speech every 20ms and are then compressed for transmission at a desired bitrate between 3.2kbps and 9.2kbps. On the other end, a generative model uses those features to recreate the speech signal. Lyra harnesses the power of new natural-sounding generative models to maintain the low bitrate of parametric codecs w
This is the source code repository for RE2, a regular expression library. For documentation about how to install and use RE2, visit https://github.com/google/re2/. The short version is: make make test make install make testinstall Building RE2 requires Abseil (https://github.com/abseil/abseil-cpp) to be installed on your system. Building the testing for RE2 requires GoogleTest (https://github.com/
The Common Expression Language (CEL) implements common semantics for expression evaluation, enabling different applications to more easily interoperate. Key Applications Security policy: organizations have complex infrastructure and need common tooling to reason about the system as a whole Protocols: expressions are a useful data type and require interoperability across programming languages and p
Introduction InternetDomainName is a useful tool for parsing and manipulating domain names. It can be used as a validator, a component extractor, and as a value type for passing around domain names in a type-safe way. However, there are some aspects of InternetDomainName behavior which may be surprising, and which can lead to bugs in calling code. This document addresses these concerns. Details Pu
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